CVE-2026-26273 (GCVE-0-2026-26273)
Vulnerability from cvelistv5 – Published: 2026-02-13 21:45 – Updated: 2026-02-17 20:00
VLAI
EPSS
VEX
Title
Known affected by Account Takeover via Password Reset Token Leakage
Summary
Known is a social publishing platform. Prior to 1.6.3, a Critical Broken Authentication vulnerability exists in Known 1.6.2 and earlier. The application leaks the password reset token within a hidden HTML input field on the password reset page. This allows any unauthenticated attacker to retrieve the reset token for any user by simply querying the user's email, leading to full Account Takeover (ATO) without requiring access to the victim's email inbox. This vulnerability is fixed in 1.6.3.
Severity
9.8 (Critical)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-02-17 20:00 UTC
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/idno/known/security/advisories… | x_refsource_CONFIRM |
| https://github.com/idno/known/commit/8439a0747471… | x_refsource_MISC |
| https://github.com/idno/known/releases/tag/1.6.3 | x_refsource_MISC |
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FKIE_CVE-2026-26273
Vulnerability from fkie_nvd - Published: 2026-02-13 22:16 - Updated: 2026-06-17 10:26
Severity
Summary
Known is a social publishing platform. Prior to 1.6.3, a Critical Broken Authentication vulnerability exists in Known 1.6.2 and earlier. The application leaks the password reset token within a hidden HTML input field on the password reset page. This allows any unauthenticated attacker to retrieve the reset token for any user by simply querying the user's email, leading to full Account Takeover (ATO) without requiring access to the victim's email inbox. This vulnerability is fixed in 1.6.3.
References
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GHSA-78WQ-6GCV-W28R
Vulnerability from github – Published: 2026-02-13 22:49 – Updated: 2026-02-13 22:49
VLAI
Summary
Known affected by Account Takeover via Password Reset Token Leakage
Details
Summary
A Critical Broken Authentication vulnerability exists in Known 1.6.2. The application leaks the password reset token within a hidden HTML input field on the password reset page. This allows any unauthenticated attacker to retrieve the reset token for any user by simply querying the user's email, leading to full Account Takeover (ATO) without requiring access to the victim's email inbox.
Details
The vulnerability occurs within the password reset flow. When a reset is requested, the application generates a verification code. However, the subsequent reset page (/account/password/reset/) incorrectly reflects this code back to the client in the HTML source code.
Specifically, the sensitive token is embedded in:
Because this page is accessible via a GET request using the victim's email as a parameter, an attacker can programmatically extract the token.
PoC
- The attacker asks for a password reset for the victim
-
The attacker makes the following curl command on the terminal using the victim's email, and is able to get the code that was sent as an hidden field in the HTML.
-
With this code, the attacker is able to use it in order to reset the victim password.
- The attacker is able to login with the new password.
Impact
- An attacker can compromise any account on the platform, including administrative accounts, resulting in total loss of Confidentiality, Integrity, and Availability.
Severity
9.8 (Critical)
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"severity": "CRITICAL"
},
"details": "### Summary\nA Critical Broken Authentication vulnerability exists in Known 1.6.2. The application leaks the password reset token within a hidden HTML input field on the password reset page. This allows any unauthenticated attacker to retrieve the reset token for any user by simply querying the user\u0027s email, leading to full Account Takeover (ATO) without requiring access to the victim\u0027s email inbox.\n\n### Details\nThe vulnerability occurs within the password reset flow. When a reset is requested, the application generates a verification code. However, the subsequent reset page (/account/password/reset/) incorrectly reflects this code back to the client in the HTML source code.\n\nSpecifically, the sensitive token is embedded in:\n\u003cinput type=\"hidden\" name=\"code\" value=\"[SECRET_TOKEN]\"\u003e\n\nBecause this page is accessible via a GET request using the victim\u0027s email as a parameter, an attacker can programmatically extract the token.\n\n### PoC\n1. The attacker asks for a password reset for the victim\n\n\u003cimg width=\"1328\" height=\"580\" alt=\"image\" src=\"https://github.com/user-attachments/assets/0197907e-f10b-4e6d-989e-f25c408862cd\" /\u003e\n\n\u003cimg width=\"1139\" height=\"452\" alt=\"image(1)\" src=\"https://github.com/user-attachments/assets/9a317b27-b56a-4663-9965-d3e660713f4e\" /\u003e\n\n\n2. The attacker makes the following curl command on the terminal using the victim\u0027s email, and is able to get the code that was sent as an hidden field in the HTML.\n\u003cimg width=\"917\" height=\"220\" alt=\"image(2)\" src=\"https://github.com/user-attachments/assets/af89ba3b-de56-4437-84b3-c1feb56d2348\" /\u003e\n\n3. With this code, the attacker is able to use it in order to reset the victim password.\n\u003cimg width=\"1335\" height=\"711\" alt=\"image(3)\" src=\"https://github.com/user-attachments/assets/498b8a2e-9eb2-4b50-bc35-26b0f2764c8d\" /\u003e\n\n\u003cimg width=\"1258\" height=\"524\" alt=\"image(4)\" src=\"https://github.com/user-attachments/assets/d1304dc3-bf56-4ec7-920c-ecce502db6b0\" /\u003e\n\n4. The attacker is able to login with the new password.\n\n\u003cimg width=\"1514\" height=\"631\" alt=\"image(5)\" src=\"https://github.com/user-attachments/assets/2533032e-6f0d-45c8-9fe1-881bfedebcc4\" /\u003e\n\n\u003cimg width=\"1528\" height=\"647\" alt=\"image(6)\" src=\"https://github.com/user-attachments/assets/a6e9144c-cc96-493d-8780-9156c299a192\" /\u003e\n\n\n\n### Impact\n- An attacker can compromise any account on the platform, including administrative accounts, resulting in total loss of Confidentiality, Integrity, and Availability.",
"id": "GHSA-78wq-6gcv-w28r",
"modified": "2026-02-13T22:49:27Z",
"published": "2026-02-13T22:49:27Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/idno/known/security/advisories/GHSA-78wq-6gcv-w28r"
},
{
"type": "WEB",
"url": "https://github.com/idno/known/commit/8439a0747471559fb1ea9f074b929d390f27e66a"
},
{
"type": "PACKAGE",
"url": "https://github.com/idno/known"
},
{
"type": "WEB",
"url": "https://github.com/idno/known/releases/tag/1.6.3"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "Known affected by Account Takeover via Password Reset Token Leakage"
}
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.